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Senior Analytics Engineer, People Data

Anduril· Business Operations : Business Operations : Analytics
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Hybrid (Boston, MA; Costa Mesa, CA)$166k - $220kFull-timePosted 4mo ago

About the role

Role focused on building and maintaining robust data infrastructure for People Data & Analytics, transforming HR data into analytics-ready datasets to empower People Analysts and stakeholders.

Responsibilities

  • Design, build, and optimize robust ETL/ELT pipelines to reliably ingest, integrate, and transform diverse people data from various HR systems (HRIS, ATS, LMS, etc.) into our data platform.
  • Develop, maintain, and govern scalable and secure data models, schemas, and ontologies specifically for people analytics, ensuring data quality, consistency, and accessibility for downstream consumption.
  • Contribute to the strategic design, development, and evolution of our people data platform and tooling, advocating for engineering best practices, automation, and a scalable analytics ecosystem (e.g., leveraging SQLMesh, Iceberg, Flyte).
  • Partner closely with People Analysts, HR Business Partners, and other stakeholders to understand analytical needs and translate them into robust data solutions, providing well-structured, documented, and reliable datasets.
  • Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure reliability and integrity of people data across all systems.
  • Continuously monitor the performance of data pipelines and models, identifying bottlenecks and implementing solutions to ensure efficiency and scalability.
  • Create and maintain comprehensive documentation for data pipelines, models, and processes, and champion data engineering best practices (e.g., version control, testing, CI/CD).
  • Implement and enforce strict data security measures and ensure all data handling practices comply with internal policies and external regulations (e.g., GDPR, CCPA).
  • Collaborate with broader enterprise analytics and data engineering teams to align on data architecture standards, integrate people data with other business domains, and contribute to the evolution of the company data platform.

Qualifications

  • 5+ years of progressive experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and data infrastructure.
  • Expert-level proficiency in SQL for complex data manipulation and querying, and advanced Python for scripting, data processing, and automation.
  • Extensive experience with cloud-based data warehousing solutions (e.g., Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake technologies (e.g., AWS S3, Azure Data Lake Storage).
  • Deep understanding and proven experience in designing, implementing, and maintaining robust data models (e.g., dimensional modeling, Kimball methodology) for analytical purposes.
  • Hands-on experience building and optimizing complex ETL/ELT processes and data pipelines using modern tools such as dbt, Apache Airflow, Flyte, Dagster, or similar orchestration platforms.
  • Excellent communication skills, both written and verbal, with the ability to translate technical concepts for non-technical stakeholders and collaborate effectively across diverse teams.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
  • Strong technical foundation in data engineering, with expertise in SQL, Python, and experience working with cloud-based data platforms (e.g., AWS, GCP, Azure).

Skills

Required:SQLPythonCloud Data WarehousingData ModelingETL/ELT Tools

Benefits

  • Comprehensive, competitive benefits package (available at little to no cost to employees).
Last updated Jul 8, 2026. Interested? Apply on the company site.

About Anduril

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